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Artificial Intelligence for Insurance Fraud Detection: Predictive Models and Risk Analysis explores the transformative role of AI in combating insurance fraud. Covering key topics such as risk management, data privacy, and compliance, the book provides an in-depth analysis of machine learning, deep learning, and anomaly detection techniques for fraud identification. It delves into ensemble and hybrid models, NLP for textual fraud detection, and Explainable AI (XAI) for transparent decision-making. Blockchain and smart contracts are also discussed as innovative fraud prevention tools. With…mehr

Produktbeschreibung
Artificial Intelligence for Insurance Fraud Detection: Predictive Models and Risk Analysis explores the transformative role of AI in combating insurance fraud. Covering key topics such as risk management, data privacy, and compliance, the book provides an in-depth analysis of machine learning, deep learning, and anomaly detection techniques for fraud identification. It delves into ensemble and hybrid models, NLP for textual fraud detection, and Explainable AI (XAI) for transparent decision-making. Blockchain and smart contracts are also discussed as innovative fraud prevention tools. With real-world case studies and emerging trends, this book serves as a comprehensive guide for insurance professionals, data scientists, and AI researchers aiming to enhance fraud detection with cutting-edge technologies.
Autorenporträt
Shravan Kumar Joginipalli: a visionary technology leader driving AI innovation in InsurTech. A Senior IEEE Member and industry advisor, he revolutionized claims processing during disasters, ensuring faster, data-driven payouts. A mentor, researcher, and global judge, he pioneers AI-driven risk solutions, shaping the future of insurance technology.